Transcription profiles of non-immortalized breast cancer cell lines - Holland James F; Fernandez-Cobo Mariana; Pogo Beatriz GT (BMC Cancer, 2006)
Abstract Background Searches for differentially expressed genes in tumours have made extensive use of array technology. Most samples have been obtained from tumour biopsies or from established tumour-derived cell lines. Here we compare cultures of non-immortalized breast cancer cells, normal non-immortalized breast cells and immortalized normal and breast cancer cells to identify which elements of a defined set of well-known cancer-related genes are differentially expressed. Methods Cultures of cells from pleural effusions or ascitic fluids from breast cancer patients (MSSMs) were used in addition to commercially-available normal breast epithelial cells (HMECs), established breast cancer cell lines (T-est) and established normal breast cells (N-est). The Atlas Human Cancer 1.2 cDNA expression array was employed. The data obtained were analysed using widely-available statistical and clustering software and further validated through real-time PCR. Results According to Significance Analysis of Microarray (SAM) and AtlasImage software, 48 genes differed at least 2-fold in adjusted intensities between HMECs and MSSMs (p < 0.01). Some of these genes have already been directly linked with breast cancer, metastasis and malignant progression, whilst others encode receptors linked to signal transduction pathways or are otherwise related to cell proliferation. Fifty genes showed at least a 2.5-fold difference between MSSMs and T-est cells according to AtlasImage, 2-fold according to SAM. Most of these classified as genes related to metabolism and cell communication. Conclusion The expression profiles of 1176 genes were determined in finite life-span cultures of metastatic breast cancer cells and of normal breast cells. Significant differences were detected between the finite life-span breast cancer cell cultures and the established breast cancer cell lines. These data suggest caution in extrapolating information from established lines for application to clinical cancer research.